Книга Incrementally Trainable Statistical Approach to Information Extraction - Based on Token Classification and Rich Context Model Christian Siefkes

Incrementally Trainable Statistical Approach to Information Extraction - Based on Token Classification and Rich Context Model

Автор: Christian Siefkes
Език: Английски език
Корици: С меки корици
Издател: VDM Verlag Dr. Mueller E.K.
Наличност: Външен склад
Изпращаме след 14-21 дни
79.66 155.81 лв
Most of the information stored in digital form is hidden in natural§language texts. The purpose of I...

Информация за книгата

Автор
Език
Английски език
Корици
Книга - С меки корици
Издадена
2008
страници
220
EAN
9783639001464
ISBN
363900146X
Enbook ID
06810329
Теглоt
299
Размери
152 x 229 x 12

Пълно описание

Most of the information stored in digital form is hidden in natural§language texts. The purpose of Information Extraction (IE) is to find§desired pieces of information in unstructured or weakly structured texts§and store them in a form that is suitable for automatic querying and§processing.§§This book presents a innovative approach to statistical information§extraction. It introduces a new algorithm which supports functionality not§available in previous IE systems, such as interactive incremental training§to reduce the human training effort. The system also utilizes new sources§of information, employing rich tree-based context representations to§combine document structure (HTML or XML markup) with linguistic and§semantic information.§§The resulting IE system is designed as a generic framework for statistical§information extraction. All core components can be modified or exchanged§independently of each other.§§This book is of interest for professionals who have to deal with large§amounts of weakly structured information and seek ways to automate this§process, as well as for researchers and practitioners active in the fields§of text mining and text classification.

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